Neutron stimulated emission computed tomography (NSECT) is being proposed as an experimental technique to diagnose iron overload in patients. Proof-of-concept experiments have suggested that NSECT may have potential to make a non-invasive diagnosis of iron overload in a clinical system. The technique's sensitivity to high concentrations of iron combined with tomographic acquisition ability gives it a unique advantage over other competing modalities. While early experiments have demonstrated the efficacy of detecting samples with high concentrations of iron, a tomography application for patient diagnosis has never been tested. As with any other tomography system, the performance of NSECT will depend greatly on the acquisition parameters that are used to scan the patient. In order to determine the best acquisition geometry for a clinical system, it is important to evaluate and understand the effects of varying each individual acquisition parameter on the accuracy of the reconstructed image. This research work proposes to use Monte-Carlo simulations to optimize a clinical NSECT system for iron overload diagnosis.Simulations of two NSECT systems have been designed in GEANT4, a spectroscopy system to detect uniform concentrations of iron in the liver, and a tomography system to detect non-uniform iron overload. Each system has been used to scan simulated samples of both disease models in humans to determine the best scanning strategy for each. The optimal scanning strategy is defined as the combination of parameters that provides maximum accuracy with minimum radiation dose. Evaluation of accuracy is performed through ROC analysis of the reconstructed spectrums and images. For the spectroscopy system, the optimal acquisition geometry is defined in terms of the number of neutrons required to detect a clinically relevant concentration of iron. For the tomography system, the optimal scanning strategy is defined in terms of the number of neutrons and the number of spatial and angular translation steps used during acquisition. Patient dose for each simulated system is calculated by measuring the energy deposited by the neutron beam in the liver and surrounding body tissue. Simulation results indicate that both scanning systems can detect wet iron concentrations of 5 mg/g or higher. Spectroscopic scanning with sufficient accuracy is possible with 1 million neutrons per scan, corresponding to a patient dose of 0.02 mSv. Tomographic scanning requires 8 angles that sample the image matrix at 1 cm projection intervals with 4 million neutrons per projection, which corresponds to a total body dose of 0.56 mSv. The research performed for this dissertation has two important outcomes. First, it demonstrates that NSECT has the clinical potential for iron overload diagnosis in patients. Second, it provides a validated simulation of the NSECT system which can be used to guide future development and experimental implementation of the technique.